Kaustubh Supekar
- Cognitive Neuroscience top 2%
- Radiology, Nuclear Medicine and Imaging top 5%
- Psychiatry and Mental health top 5%
- Genetics
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Lucina Q. UddinVinod MenonMichael D. GreiciusKatherine E. PraterHitha AminAmirah KhouzamCharles J. LynchJennifer M. Phillips
- Topics
- Functional Brain Connectivity Studies (4 papers)Biomedical Text Mining and Ontologies (4 papers)Service-Oriented Architecture and Web Services (3 papers)
- Partner nations
- United States
In The Last Decade
Kaustubh Supekar
9 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Cognitive Neuroscience 1.0k
- Radiology, Nuclear Medicine and Imaging 304
- Psychiatry and Mental health 218
- Genetics 111
- Experimental and Cognitive Psychology 107
Countries citing papers authored by Kaustubh Supekar
This map shows the geographic impact of Kaustubh Supekar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kaustubh Supekar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaustubh Supekar more than expected).
Fields of papers citing papers by Kaustubh Supekar
This network shows the impact of papers produced by Kaustubh Supekar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kaustubh Supekar. The network helps show where Kaustubh Supekar may publish in the future.
Co-authorship network of co-authors of Kaustubh Supekar
This figure shows the co-authorship network connecting the top 25 collaborators of Kaustubh Supekar. A scholar is included among the top collaborators of Kaustubh Supekar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kaustubh Supekar. Kaustubh Supekar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 22 | |
| 2 | Reconceptualizing functional brain connectivity in autism from a developmental perspectivebreakdown → | 395 |
| 3 | 282 | |
| 4 | 420 | |
| 5 | Extracting subject demographic information from abstracts of randomized clinical trial reports. | 23 |
| 6 | Knowledge Zone: a public repository of peer-reviewed biomedical ontologies. | 4 |
| 7 | Combining Text Classification and Hidden Markov Modeling Techniques for Structuring Randomized Clinical Trial Abstracts | 20 |
| 8 | Topic-Specific Trust and Open Rating Systems: An Approach for Ontology Evaluation. | 13 |
| 9 | 24 |
About Kaustubh Supekar
Kaustubh Supekar is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Information Systems, having authored 9 papers that have together received 1.2k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (4 papers), Biomedical Text Mining and Ontologies (4 papers) and Service-Oriented Architecture and Web Services (3 papers). The work is most often cited by research in Cognitive Neuroscience (1.0k citations), Psychiatry and Mental health (218 citations) and Radiology, Nuclear Medicine and Imaging (304 citations). Kaustubh Supekar has collaborated with scholars based in United States. Frequent co-authors include Lucina Q. Uddin, Vinod Menon, Michael D. Greicius, Katherine E. Prater, Hitha Amin, Amirah Khouzam, Charles J. Lynch, Jennifer M. Phillips, Alan M. Garber and Rong Xu. Their work appears in journals such as PLoS ONE, NeuroImage and Biological Psychiatry.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.